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@tensorflow/tfjs-core

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Hardware-accelerated JavaScript library for machine intelligence

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/** * @license * Copyright 2020 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ import {ENGINE} from '../engine'; import {MaxPoolGrad, MaxPoolGradAttrs, MaxPoolGradInputs} from '../kernel_names'; import {NamedAttrMap} from '../kernel_registry'; import {Tensor4D} from '../tensor'; import {NamedTensorMap} from '../tensor_types'; import {convertToTensor} from '../tensor_util_env'; import {TensorLike} from '../types'; import * as util from '../util'; import {op} from './operation'; /** * Computes the backprop of a 2D max pool. * * @param dy The dy error, of rank 4 or rank 3 of shape * [batchSize, height, width, channels]. If rank 3, batch of 1 is * assumed. * @param input The original input image, of rank 4, of shape * [batchSize, height, width, channels]. * @param output The original output image, of rank 4, of shape * [batchSize, outHeight, outWidth, channels]. * @param filterSize The filter size: `[filterHeight, filterWidth]`. If * `filterSize` is a single number, then `filterHeight == filterWidth`. * @param strides The strides of the pooling: `[strideHeight, strideWidth]`. If * `strides` is a single number, then `strideHeight == strideWidth`. * @param pad A string from: 'same', 'valid'. The type of padding algorithm * used in the forward prop of the op. * @param dimRoundingMode A string from: 'ceil', 'round', 'floor'. If none is * provided, it will default to truncate. */ function maxPoolGrad_( dy: Tensor4D|TensorLike, input: Tensor4D|TensorLike, output: Tensor4D|TensorLike, filterSize: [number, number]|number, strides: [number, number]|number, pad: 'valid'|'same'|number, dimRoundingMode?: 'floor'|'round'|'ceil'): Tensor4D { const $dy = convertToTensor(dy, 'dy', 'maxPoolGrad'); const $input = convertToTensor(input, 'input', 'maxPoolGrad'); const $output = convertToTensor(output, 'output', 'maxPoolGrad'); util.assert( $input.rank === $dy.rank, () => `Rank of input (${$input.rank}) does not match rank of dy ` + `(${$dy.rank})`); util.assert( $dy.rank === 4, () => `Error in maxPoolGrad: dy must be rank 4 but got rank ` + `${$dy.rank}.`); util.assert( $input.rank === 4, () => `Error in maxPoolGrad: input must be rank 4 but got rank ` + `${$input.rank}.`); if (dimRoundingMode != null) { util.assert( util.isInt(pad as number), () => `Error in maxPoolGrad: pad must be an integer when using, ` + `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`); } const inputs: MaxPoolGradInputs = {dy: $dy, input: $input, output: $output}; const attrs: MaxPoolGradAttrs = {filterSize, strides, pad, dimRoundingMode}; // tslint:disable-next-line: no-unnecessary-type-assertion return ENGINE.runKernel( MaxPoolGrad, inputs as {} as NamedTensorMap, attrs as {} as NamedAttrMap) as Tensor4D; } export const maxPoolGrad = op({maxPoolGrad_});